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<title>Doxygen: pcl::SpinImageEstimation&lt; PointInT, PointNT, PointOutT &gt; 模板类 参考</title>
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<a href="#pub-types">Public 类型</a> &#124;
<a href="#pub-methods">Public 成员函数</a> &#124;
<a href="#pro-methods">Protected 成员函数</a> &#124;
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<div class="title">pcl::SpinImageEstimation&lt; PointInT, PointNT, PointOutT &gt; 模板类 参考</div>  </div>
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<p>Estimates spin-image descriptors in the given input points.  
 <a href="classpcl_1_1_spin_image_estimation.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="spin__image_8h_source.html">spin_image.h</a>&gt;</code></p>
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类 pcl::SpinImageEstimation&lt; PointInT, PointNT, PointOutT &gt; 继承关系图:</div>
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 <div class="center">
  <img src="classpcl_1_1_spin_image_estimation.png" usemap="#pcl::SpinImageEstimation_3C_20PointInT_2C_20PointNT_2C_20PointOutT_20_3E_map" alt=""/>
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<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public 类型</h2></td></tr>
<tr class="memitem:a1584a8e246da5c196994f866e328be57"><td class="memItemLeft" align="right" valign="top"><a id="a1584a8e246da5c196994f866e328be57"></a>
typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1_spin_image_estimation.html">SpinImageEstimation</a>&lt; PointInT, PointNT, PointOutT &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>Ptr</b></td></tr>
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<tr class="memitem:a47f05f64d22208fad3e3834c8a96e59b"><td class="memItemLeft" align="right" valign="top"><a id="a47f05f64d22208fad3e3834c8a96e59b"></a>
typedef boost::shared_ptr&lt; const <a class="el" href="classpcl_1_1_spin_image_estimation.html">SpinImageEstimation</a>&lt; PointInT, PointNT, PointOutT &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>ConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_feature.html">Feature</a>&lt; PointInT, PointOutT &gt;::<a class="el" href="classpcl_1_1_point_cloud.html">PointCloudOut</a>&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudOut</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointNT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudN</b></td></tr>
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typedef PointCloudN::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudNPtr</b></td></tr>
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typedef PointCloudN::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudNConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointInT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudIn</b></td></tr>
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typedef PointCloudIn::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudInPtr</b></td></tr>
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typedef PointCloudIn::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudInConstPtr</b></td></tr>
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<tr class="inherit_header pub_types_classpcl_1_1_feature"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classpcl_1_1_feature')"><img src="closed.png" alt="-"/>&#160;Public 类型 继承自 <a class="el" href="classpcl_1_1_feature.html">pcl::Feature&lt; PointInT, PointOutT &gt;</a></td></tr>
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typedef <a class="el" href="classpcl_1_1_p_c_l_base.html">PCLBase</a>&lt; PointInT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>BaseClass</b></td></tr>
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typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1_feature.html">Feature</a>&lt; PointInT, PointOutT &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>Ptr</b></td></tr>
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typedef boost::shared_ptr&lt; const <a class="el" href="classpcl_1_1_feature.html">Feature</a>&lt; PointInT, PointOutT &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>ConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1search_1_1_search.html">pcl::search::Search</a>&lt; PointInT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>KdTree</b></td></tr>
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typedef <a class="el" href="classpcl_1_1search_1_1_search.html">pcl::search::Search</a>&lt; PointInT &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>KdTreePtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointInT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudIn</b></td></tr>
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typedef PointCloudIn::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudInPtr</b></td></tr>
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typedef PointCloudIn::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudInConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointOutT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudOut</b></td></tr>
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typedef boost::function&lt; int(size_t, double, std::vector&lt; int &gt; &amp;, std::vector&lt; float &gt; &amp;)&gt;&#160;</td><td class="memItemRight" valign="bottom"><b>SearchMethod</b></td></tr>
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typedef boost::function&lt; int(const <a class="el" href="classpcl_1_1_point_cloud.html">PointCloudIn</a> &amp;cloud, size_t index, double, std::vector&lt; int &gt; &amp;, std::vector&lt; float &gt; &amp;)&gt;&#160;</td><td class="memItemRight" valign="bottom"><b>SearchMethodSurface</b></td></tr>
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<tr class="inherit_header pub_types_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Public 类型 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointInT &gt;</a></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointInT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloud</b></td></tr>
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typedef PointCloud::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudPtr</b></td></tr>
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typedef PointCloud::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudConstPtr</b></td></tr>
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typedef boost::shared_ptr&lt; <a class="el" href="structpcl_1_1_point_indices.html">PointIndices</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointIndicesPtr</b></td></tr>
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typedef boost::shared_ptr&lt; <a class="el" href="structpcl_1_1_point_indices.html">PointIndices</a> const &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointIndicesConstPtr</b></td></tr>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public 成员函数</h2></td></tr>
<tr class="memitem:ab66e696b17513a417f97e39aa399f73e"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#ab66e696b17513a417f97e39aa399f73e">SpinImageEstimation</a> (unsigned int image_width=8, double support_angle_cos=0.0, unsigned int min_pts_neighb=0)</td></tr>
<tr class="memdesc:ab66e696b17513a417f97e39aa399f73e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructs empty spin image estimator.  <a href="classpcl_1_1_spin_image_estimation.html#ab66e696b17513a417f97e39aa399f73e">更多...</a><br /></td></tr>
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virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#afe0a39b45ca455a2875caf0d84186b2c">~SpinImageEstimation</a> ()</td></tr>
<tr class="memdesc:afe0a39b45ca455a2875caf0d84186b2c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty destructor <br /></td></tr>
<tr class="separator:afe0a39b45ca455a2875caf0d84186b2c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a93f3f5586e8f01b01a2ea95f77b5d7d6"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#a93f3f5586e8f01b01a2ea95f77b5d7d6">setImageWidth</a> (unsigned int bin_count)</td></tr>
<tr class="memdesc:a93f3f5586e8f01b01a2ea95f77b5d7d6"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets spin-image resolution.  <a href="classpcl_1_1_spin_image_estimation.html#a93f3f5586e8f01b01a2ea95f77b5d7d6">更多...</a><br /></td></tr>
<tr class="separator:a93f3f5586e8f01b01a2ea95f77b5d7d6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aec8636459345b81d562ba9bab97dadfd"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#aec8636459345b81d562ba9bab97dadfd">setSupportAngle</a> (double support_angle_cos)</td></tr>
<tr class="memdesc:aec8636459345b81d562ba9bab97dadfd"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets the maximum angle for the point normal to get to support region.  <a href="classpcl_1_1_spin_image_estimation.html#aec8636459345b81d562ba9bab97dadfd">更多...</a><br /></td></tr>
<tr class="separator:aec8636459345b81d562ba9bab97dadfd"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a99c85206d6eabdbaf3aa4dd989d930a7"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#a99c85206d6eabdbaf3aa4dd989d930a7">setMinPointCountInNeighbourhood</a> (unsigned int min_pts_neighb)</td></tr>
<tr class="memdesc:a99c85206d6eabdbaf3aa4dd989d930a7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets minimal points count for spin image computation.  <a href="classpcl_1_1_spin_image_estimation.html#a99c85206d6eabdbaf3aa4dd989d930a7">更多...</a><br /></td></tr>
<tr class="separator:a99c85206d6eabdbaf3aa4dd989d930a7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa847219e3000ed6a1dd73509bcc318e4"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#aa847219e3000ed6a1dd73509bcc318e4">setInputNormals</a> (const PointCloudNConstPtr &amp;normals)</td></tr>
<tr class="memdesc:aa847219e3000ed6a1dd73509bcc318e4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the input dataset that contains the point normals of the input XYZ dataset given by <a class="el" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a>  <a href="classpcl_1_1_spin_image_estimation.html#aa847219e3000ed6a1dd73509bcc318e4">更多...</a><br /></td></tr>
<tr class="separator:aa847219e3000ed6a1dd73509bcc318e4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a12e76226cf145a57973c0b37bb80c3f1"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#a12e76226cf145a57973c0b37bb80c3f1">setRotationAxis</a> (const PointNT &amp;axis)</td></tr>
<tr class="memdesc:a12e76226cf145a57973c0b37bb80c3f1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets single vector a rotation axis for all input points.  <a href="classpcl_1_1_spin_image_estimation.html#a12e76226cf145a57973c0b37bb80c3f1">更多...</a><br /></td></tr>
<tr class="separator:a12e76226cf145a57973c0b37bb80c3f1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af5a269fd1b1606d4fb90329f7efd5e2a"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#af5a269fd1b1606d4fb90329f7efd5e2a">setInputRotationAxes</a> (const PointCloudNConstPtr &amp;axes)</td></tr>
<tr class="memdesc:af5a269fd1b1606d4fb90329f7efd5e2a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets array of vectors as rotation axes for input points.  <a href="classpcl_1_1_spin_image_estimation.html#af5a269fd1b1606d4fb90329f7efd5e2a">更多...</a><br /></td></tr>
<tr class="separator:af5a269fd1b1606d4fb90329f7efd5e2a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a50add0c928dada110031d1f95d9d8290"><td class="memItemLeft" align="right" valign="top"><a id="a50add0c928dada110031d1f95d9d8290"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#a50add0c928dada110031d1f95d9d8290">useNormalsAsRotationAxis</a> ()</td></tr>
<tr class="memdesc:a50add0c928dada110031d1f95d9d8290"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets input normals as rotation axes (default setting). <br /></td></tr>
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<tr class="memitem:a77bac69302ebb759336dfa711dfe24c9"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#a77bac69302ebb759336dfa711dfe24c9">setAngularDomain</a> (bool is_angular=true)</td></tr>
<tr class="memdesc:a77bac69302ebb759336dfa711dfe24c9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets/unsets flag for angular spin-image domain.  <a href="classpcl_1_1_spin_image_estimation.html#a77bac69302ebb759336dfa711dfe24c9">更多...</a><br /></td></tr>
<tr class="separator:a77bac69302ebb759336dfa711dfe24c9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5e371335fa14ddf04196bf76d720645b"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#a5e371335fa14ddf04196bf76d720645b">setRadialStructure</a> (bool is_radial=true)</td></tr>
<tr class="memdesc:a5e371335fa14ddf04196bf76d720645b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Sets/unsets flag for radial spin-image structure.  <a href="classpcl_1_1_spin_image_estimation.html#a5e371335fa14ddf04196bf76d720645b">更多...</a><br /></td></tr>
<tr class="separator:a5e371335fa14ddf04196bf76d720645b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classpcl_1_1_feature"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1_feature')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1_feature.html">pcl::Feature&lt; PointInT, PointOutT &gt;</a></td></tr>
<tr class="memitem:a96497e27e1087c0b1e07c8ae84aea152 inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="a96497e27e1087c0b1e07c8ae84aea152"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a96497e27e1087c0b1e07c8ae84aea152">Feature</a> ()</td></tr>
<tr class="memdesc:a96497e27e1087c0b1e07c8ae84aea152 inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor. <br /></td></tr>
<tr class="separator:a96497e27e1087c0b1e07c8ae84aea152 inherit pub_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a147e6286fc98646910c4b6751278038f inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="a147e6286fc98646910c4b6751278038f"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a147e6286fc98646910c4b6751278038f">~Feature</a> ()</td></tr>
<tr class="memdesc:a147e6286fc98646910c4b6751278038f inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty destructor <br /></td></tr>
<tr class="separator:a147e6286fc98646910c4b6751278038f inherit pub_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a14fbb05e0e8f1d1ec766a50353f3c224 inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a14fbb05e0e8f1d1ec766a50353f3c224">setSearchSurface</a> (const PointCloudInConstPtr &amp;cloud)</td></tr>
<tr class="memdesc:a14fbb05e0e8f1d1ec766a50353f3c224 inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset. This is optional, if this is not set, it will only use the data in the input cloud to estimate the features. This is useful when you only need to compute the features for a downsampled cloud.  <a href="classpcl_1_1_feature.html#a14fbb05e0e8f1d1ec766a50353f3c224">更多...</a><br /></td></tr>
<tr class="separator:a14fbb05e0e8f1d1ec766a50353f3c224 inherit pub_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a09320ff2025be07c1e4a378d88588e8d inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="a09320ff2025be07c1e4a378d88588e8d"></a>
PointCloudInConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a09320ff2025be07c1e4a378d88588e8d">getSearchSurface</a> () const</td></tr>
<tr class="memdesc:a09320ff2025be07c1e4a378d88588e8d inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the surface point cloud dataset. <br /></td></tr>
<tr class="separator:a09320ff2025be07c1e4a378d88588e8d inherit pub_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ace1caca622f06eee8ad1911228324792 inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#ace1caca622f06eee8ad1911228324792">setSearchMethod</a> (const KdTreePtr &amp;tree)</td></tr>
<tr class="memdesc:ace1caca622f06eee8ad1911228324792 inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the search object.  <a href="classpcl_1_1_feature.html#ace1caca622f06eee8ad1911228324792">更多...</a><br /></td></tr>
<tr class="separator:ace1caca622f06eee8ad1911228324792 inherit pub_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acc850056d252306c48c481e4bbee1821 inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="acc850056d252306c48c481e4bbee1821"></a>
KdTreePtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#acc850056d252306c48c481e4bbee1821">getSearchMethod</a> () const</td></tr>
<tr class="memdesc:acc850056d252306c48c481e4bbee1821 inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the search method used. <br /></td></tr>
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<tr class="memitem:a86004b18e77cc0c38a1a33fbd43fb760 inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="a86004b18e77cc0c38a1a33fbd43fb760"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a86004b18e77cc0c38a1a33fbd43fb760">getSearchParameter</a> () const</td></tr>
<tr class="memdesc:a86004b18e77cc0c38a1a33fbd43fb760 inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the internal search parameter. <br /></td></tr>
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<tr class="memitem:a50129bc51cb240eca42df9963f7ac0c0 inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a50129bc51cb240eca42df9963f7ac0c0">setKSearch</a> (int k)</td></tr>
<tr class="memdesc:a50129bc51cb240eca42df9963f7ac0c0 inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the number of k nearest neighbors to use for the feature estimation.  <a href="classpcl_1_1_feature.html#a50129bc51cb240eca42df9963f7ac0c0">更多...</a><br /></td></tr>
<tr class="separator:a50129bc51cb240eca42df9963f7ac0c0 inherit pub_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a94cce071beee358359b14db2edcc62ae inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="a94cce071beee358359b14db2edcc62ae"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a94cce071beee358359b14db2edcc62ae">getKSearch</a> () const</td></tr>
<tr class="memdesc:a94cce071beee358359b14db2edcc62ae inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">get the number of k nearest neighbors used for the feature estimation. <br /></td></tr>
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<tr class="memitem:a44829319486a2dc415a4e068dc55c577 inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a44829319486a2dc415a4e068dc55c577">setRadiusSearch</a> (double radius)</td></tr>
<tr class="memdesc:a44829319486a2dc415a4e068dc55c577 inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation.  <a href="classpcl_1_1_feature.html#a44829319486a2dc415a4e068dc55c577">更多...</a><br /></td></tr>
<tr class="separator:a44829319486a2dc415a4e068dc55c577 inherit pub_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac62f459672f3ca0e986e495a9220b268 inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="ac62f459672f3ca0e986e495a9220b268"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#ac62f459672f3ca0e986e495a9220b268">getRadiusSearch</a> () const</td></tr>
<tr class="memdesc:ac62f459672f3ca0e986e495a9220b268 inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the sphere radius used for determining the neighbors. <br /></td></tr>
<tr class="separator:ac62f459672f3ca0e986e495a9220b268 inherit pub_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad5b1fa9612da40e738b1d99252c5ff2f inherit pub_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#ad5b1fa9612da40e738b1d99252c5ff2f">compute</a> (<a class="el" href="classpcl_1_1_point_cloud.html">PointCloudOut</a> &amp;output)</td></tr>
<tr class="memdesc:ad5b1fa9612da40e738b1d99252c5ff2f inherit pub_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Base method for feature estimation for all points given in &lt;setInputCloud (), setIndices ()&gt; using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()  <a href="classpcl_1_1_feature.html#ad5b1fa9612da40e738b1d99252c5ff2f">更多...</a><br /></td></tr>
<tr class="separator:ad5b1fa9612da40e738b1d99252c5ff2f inherit pub_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointInT &gt;</a></td></tr>
<tr class="memitem:af4fbc5eb005057f8a0fc6d60bde595df inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="af4fbc5eb005057f8a0fc6d60bde595df"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#af4fbc5eb005057f8a0fc6d60bde595df">PCLBase</a> ()</td></tr>
<tr class="memdesc:af4fbc5eb005057f8a0fc6d60bde595df inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor. <br /></td></tr>
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<tr class="memitem:a7a6dd7a91275d7737cf1b18005b47244 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a7a6dd7a91275d7737cf1b18005b47244"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a7a6dd7a91275d7737cf1b18005b47244">PCLBase</a> (const <a class="el" href="classpcl_1_1_p_c_l_base.html">PCLBase</a> &amp;base)</td></tr>
<tr class="memdesc:a7a6dd7a91275d7737cf1b18005b47244 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Copy constructor. <br /></td></tr>
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<tr class="memitem:ad5d6846e98e59c37dcc3dc9958d53966 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="ad5d6846e98e59c37dcc3dc9958d53966"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#ad5d6846e98e59c37dcc3dc9958d53966">~PCLBase</a> ()</td></tr>
<tr class="memdesc:ad5d6846e98e59c37dcc3dc9958d53966 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <br /></td></tr>
<tr class="separator:ad5d6846e98e59c37dcc3dc9958d53966 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1952d7101f3942bac3b69ed55c1ca7ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a> (const PointCloudConstPtr &amp;cloud)</td></tr>
<tr class="memdesc:a1952d7101f3942bac3b69ed55c1ca7ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the input dataset  <a href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">更多...</a><br /></td></tr>
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<tr class="memitem:a8cd745c4f7a792212f4fc3720b9d46ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a8cd745c4f7a792212f4fc3720b9d46ea"></a>
PointCloudConstPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a8cd745c4f7a792212f4fc3720b9d46ea">getInputCloud</a> () const</td></tr>
<tr class="memdesc:a8cd745c4f7a792212f4fc3720b9d46ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the input point cloud dataset. <br /></td></tr>
<tr class="separator:a8cd745c4f7a792212f4fc3720b9d46ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab219359de6eb34c9d51e2e976dd1a0d1 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#ab219359de6eb34c9d51e2e976dd1a0d1">setIndices</a> (const IndicesPtr &amp;indices)</td></tr>
<tr class="memdesc:ab219359de6eb34c9d51e2e976dd1a0d1 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represents the input data.  <a href="classpcl_1_1_p_c_l_base.html#ab219359de6eb34c9d51e2e976dd1a0d1">更多...</a><br /></td></tr>
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<tr class="memitem:a436c68c74b31e4dd00000adfbb11ca7c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a436c68c74b31e4dd00000adfbb11ca7c">setIndices</a> (const IndicesConstPtr &amp;indices)</td></tr>
<tr class="memdesc:a436c68c74b31e4dd00000adfbb11ca7c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represents the input data.  <a href="classpcl_1_1_p_c_l_base.html#a436c68c74b31e4dd00000adfbb11ca7c">更多...</a><br /></td></tr>
<tr class="separator:a436c68c74b31e4dd00000adfbb11ca7c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af9cc90d8364ce968566f75800d3773ca inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#af9cc90d8364ce968566f75800d3773ca">setIndices</a> (const PointIndicesConstPtr &amp;indices)</td></tr>
<tr class="memdesc:af9cc90d8364ce968566f75800d3773ca inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represents the input data.  <a href="classpcl_1_1_p_c_l_base.html#af9cc90d8364ce968566f75800d3773ca">更多...</a><br /></td></tr>
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<tr class="memitem:a930c7a6375fdf65ff8cfdb4eb4a6d996 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a930c7a6375fdf65ff8cfdb4eb4a6d996">setIndices</a> (size_t row_start, size_t col_start, size_t nb_rows, size_t nb_cols)</td></tr>
<tr class="memdesc:a930c7a6375fdf65ff8cfdb4eb4a6d996 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the indices for the points laying within an interest region of the point cloud.  <a href="classpcl_1_1_p_c_l_base.html#a930c7a6375fdf65ff8cfdb4eb4a6d996">更多...</a><br /></td></tr>
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<tr class="memitem:a058753dd4de73d3d0062fe2e452fba3c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a058753dd4de73d3d0062fe2e452fba3c"></a>
IndicesPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a058753dd4de73d3d0062fe2e452fba3c">getIndices</a> ()</td></tr>
<tr class="memdesc:a058753dd4de73d3d0062fe2e452fba3c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the vector of indices used. <br /></td></tr>
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<tr class="memitem:acae187b37230758959572ceb1e6e2045 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="acae187b37230758959572ceb1e6e2045"></a>
IndicesConstPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#acae187b37230758959572ceb1e6e2045">getIndices</a> () const</td></tr>
<tr class="memdesc:acae187b37230758959572ceb1e6e2045 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the vector of indices used. <br /></td></tr>
<tr class="separator:acae187b37230758959572ceb1e6e2045 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af7335fedb0af0930b9d1dedcb54ba201 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">const PointInT &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#af7335fedb0af0930b9d1dedcb54ba201">operator[]</a> (size_t pos) const</td></tr>
<tr class="memdesc:af7335fedb0af0930b9d1dedcb54ba201 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Override PointCloud operator[] to shorten code  <a href="classpcl_1_1_p_c_l_base.html#af7335fedb0af0930b9d1dedcb54ba201">更多...</a><br /></td></tr>
<tr class="separator:af7335fedb0af0930b9d1dedcb54ba201 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
Protected 成员函数</h2></td></tr>
<tr class="memitem:ab09ec6b20fc126a9e2f1ab19fee51286"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#ab09ec6b20fc126a9e2f1ab19fee51286">computeFeature</a> (<a class="el" href="classpcl_1_1_point_cloud.html">PointCloudOut</a> &amp;output)</td></tr>
<tr class="memdesc:ab09ec6b20fc126a9e2f1ab19fee51286"><td class="mdescLeft">&#160;</td><td class="mdescRight">Estimate the Spin Image descriptors at a set of points given by setInputWithNormals() using the surface in setSearchSurfaceWithNormals() and the spatial locator  <a href="classpcl_1_1_spin_image_estimation.html#ab09ec6b20fc126a9e2f1ab19fee51286">更多...</a><br /></td></tr>
<tr class="separator:ab09ec6b20fc126a9e2f1ab19fee51286"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a05bd9a4e042a5e212c4fac5cc589db95"><td class="memItemLeft" align="right" valign="top">virtual bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#a05bd9a4e042a5e212c4fac5cc589db95">initCompute</a> ()</td></tr>
<tr class="memdesc:a05bd9a4e042a5e212c4fac5cc589db95"><td class="mdescLeft">&#160;</td><td class="mdescRight">initializes computations specific to spin-image.  <a href="classpcl_1_1_spin_image_estimation.html#a05bd9a4e042a5e212c4fac5cc589db95">更多...</a><br /></td></tr>
<tr class="separator:a05bd9a4e042a5e212c4fac5cc589db95"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3144eb10e31eb625d1e0faaeee278e26"><td class="memItemLeft" align="right" valign="top">Eigen::ArrayXXd&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_spin_image_estimation.html#a3144eb10e31eb625d1e0faaeee278e26">computeSiForPoint</a> (int index) const</td></tr>
<tr class="memdesc:a3144eb10e31eb625d1e0faaeee278e26"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes a spin-image for the point of the scan.  <a href="classpcl_1_1_spin_image_estimation.html#a3144eb10e31eb625d1e0faaeee278e26">更多...</a><br /></td></tr>
<tr class="separator:a3144eb10e31eb625d1e0faaeee278e26"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_methods_classpcl_1_1_feature"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classpcl_1_1_feature')"><img src="closed.png" alt="-"/>&#160;Protected 成员函数 继承自 <a class="el" href="classpcl_1_1_feature.html">pcl::Feature&lt; PointInT, PointOutT &gt;</a></td></tr>
<tr class="memitem:ae6b4d5717999b6267a670dc704146fdc inherit pro_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="ae6b4d5717999b6267a670dc704146fdc"></a>
const std::string &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> () const</td></tr>
<tr class="memdesc:ae6b4d5717999b6267a670dc704146fdc inherit pro_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a string representation of the name of this class. <br /></td></tr>
<tr class="separator:ae6b4d5717999b6267a670dc704146fdc inherit pro_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab235b6b76033922b19aae91714d7e413 inherit pro_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="ab235b6b76033922b19aae91714d7e413"></a>
virtual bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#ab235b6b76033922b19aae91714d7e413">deinitCompute</a> ()</td></tr>
<tr class="memdesc:ab235b6b76033922b19aae91714d7e413 inherit pro_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">This method should get called after ending the actual computation. <br /></td></tr>
<tr class="separator:ab235b6b76033922b19aae91714d7e413 inherit pro_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa7d2ff6f0db4d63a74a3e01ad2b1f9ab inherit pro_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#aa7d2ff6f0db4d63a74a3e01ad2b1f9ab">searchForNeighbors</a> (size_t index, double parameter, std::vector&lt; int &gt; &amp;indices, std::vector&lt; float &gt; &amp;distances) const</td></tr>
<tr class="memdesc:aa7d2ff6f0db4d63a74a3e01ad2b1f9ab inherit pro_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Search for k-nearest neighbors using the spatial locator from <em>setSearchmethod</em>, and the given surface from <em>setSearchSurface</em>.  <a href="classpcl_1_1_feature.html#aa7d2ff6f0db4d63a74a3e01ad2b1f9ab">更多...</a><br /></td></tr>
<tr class="separator:aa7d2ff6f0db4d63a74a3e01ad2b1f9ab inherit pro_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9422bdfb7074f73019e32d55eeda73bb inherit pro_methods_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a9422bdfb7074f73019e32d55eeda73bb">searchForNeighbors</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">PointCloudIn</a> &amp;cloud, size_t index, double parameter, std::vector&lt; int &gt; &amp;indices, std::vector&lt; float &gt; &amp;distances) const</td></tr>
<tr class="memdesc:a9422bdfb7074f73019e32d55eeda73bb inherit pro_methods_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">Search for k-nearest neighbors using the spatial locator from <em>setSearchmethod</em>, and the given surface from <em>setSearchSurface</em>.  <a href="classpcl_1_1_feature.html#a9422bdfb7074f73019e32d55eeda73bb">更多...</a><br /></td></tr>
<tr class="separator:a9422bdfb7074f73019e32d55eeda73bb inherit pro_methods_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_methods_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Protected 成员函数 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointInT &gt;</a></td></tr>
<tr class="memitem:acceb20854934f4cf77e266eb5a44d4f0 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#acceb20854934f4cf77e266eb5a44d4f0">initCompute</a> ()</td></tr>
<tr class="memdesc:acceb20854934f4cf77e266eb5a44d4f0 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">This method should get called before starting the actual computation.  <a href="classpcl_1_1_p_c_l_base.html#acceb20854934f4cf77e266eb5a44d4f0">更多...</a><br /></td></tr>
<tr class="separator:acceb20854934f4cf77e266eb5a44d4f0 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afc426c4eebb94b7734d4fa556bff1420 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="afc426c4eebb94b7734d4fa556bff1420"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#afc426c4eebb94b7734d4fa556bff1420">deinitCompute</a> ()</td></tr>
<tr class="memdesc:afc426c4eebb94b7734d4fa556bff1420 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">This method should get called after finishing the actual computation. <br /></td></tr>
<tr class="separator:afc426c4eebb94b7734d4fa556bff1420 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pri-attribs"></a>
Private 属性</h2></td></tr>
<tr class="memitem:af788ad009ae7c9f0ad261880c9d1438d"><td class="memItemLeft" align="right" valign="top"><a id="af788ad009ae7c9f0ad261880c9d1438d"></a>
PointCloudNConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>input_normals_</b></td></tr>
<tr class="separator:af788ad009ae7c9f0ad261880c9d1438d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa9318a6c8bebcc51b27a735f87a0fdd9"><td class="memItemLeft" align="right" valign="top"><a id="aa9318a6c8bebcc51b27a735f87a0fdd9"></a>
PointCloudNConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>rotation_axes_cloud_</b></td></tr>
<tr class="separator:aa9318a6c8bebcc51b27a735f87a0fdd9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0a8563666ed008b38f0f1ecdf8bbd1b1"><td class="memItemLeft" align="right" valign="top"><a id="a0a8563666ed008b38f0f1ecdf8bbd1b1"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><b>is_angular_</b></td></tr>
<tr class="separator:a0a8563666ed008b38f0f1ecdf8bbd1b1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a474fe3fb3482303fac155755b0b110ba"><td class="memItemLeft" align="right" valign="top"><a id="a474fe3fb3482303fac155755b0b110ba"></a>
PointNT&#160;</td><td class="memItemRight" valign="bottom"><b>rotation_axis_</b></td></tr>
<tr class="separator:a474fe3fb3482303fac155755b0b110ba"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3ef9bd380aff487d46e891e8a71a9189"><td class="memItemLeft" align="right" valign="top"><a id="a3ef9bd380aff487d46e891e8a71a9189"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><b>use_custom_axis_</b></td></tr>
<tr class="separator:a3ef9bd380aff487d46e891e8a71a9189"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa9bb8cca1395380861039e3466fe3f9d"><td class="memItemLeft" align="right" valign="top"><a id="aa9bb8cca1395380861039e3466fe3f9d"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><b>use_custom_axes_cloud_</b></td></tr>
<tr class="separator:aa9bb8cca1395380861039e3466fe3f9d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9bc1b67e27e3bae37ab4d7117e57b197"><td class="memItemLeft" align="right" valign="top"><a id="a9bc1b67e27e3bae37ab4d7117e57b197"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><b>is_radial_</b></td></tr>
<tr class="separator:a9bc1b67e27e3bae37ab4d7117e57b197"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a20b90c03e800292574425cdbe572bb93"><td class="memItemLeft" align="right" valign="top"><a id="a20b90c03e800292574425cdbe572bb93"></a>
unsigned int&#160;</td><td class="memItemRight" valign="bottom"><b>image_width_</b></td></tr>
<tr class="separator:a20b90c03e800292574425cdbe572bb93"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a22965146e0fda887d35107094fd79897"><td class="memItemLeft" align="right" valign="top"><a id="a22965146e0fda887d35107094fd79897"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><b>support_angle_cos_</b></td></tr>
<tr class="separator:a22965146e0fda887d35107094fd79897"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3213fa9aa765917b2293382e65a61730"><td class="memItemLeft" align="right" valign="top"><a id="a3213fa9aa765917b2293382e65a61730"></a>
unsigned int&#160;</td><td class="memItemRight" valign="bottom"><b>min_pts_neighb_</b></td></tr>
<tr class="separator:a3213fa9aa765917b2293382e65a61730"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="inherited"></a>
额外继承的成员函数</h2></td></tr>
<tr class="inherit_header pro_attribs_classpcl_1_1_feature"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classpcl_1_1_feature')"><img src="closed.png" alt="-"/>&#160;Protected 属性 继承自 <a class="el" href="classpcl_1_1_feature.html">pcl::Feature&lt; PointInT, PointOutT &gt;</a></td></tr>
<tr class="memitem:a54032b79551164878ff59ed93b5c1dc5 inherit pro_attribs_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="a54032b79551164878ff59ed93b5c1dc5"></a>
std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a54032b79551164878ff59ed93b5c1dc5">feature_name_</a></td></tr>
<tr class="memdesc:a54032b79551164878ff59ed93b5c1dc5 inherit pro_attribs_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">The feature name. <br /></td></tr>
<tr class="separator:a54032b79551164878ff59ed93b5c1dc5 inherit pro_attribs_classpcl_1_1_feature"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af2d27cdd139bd79335008303cf68ba82 inherit pro_attribs_classpcl_1_1_feature"><td class="memItemLeft" align="right" valign="top"><a id="af2d27cdd139bd79335008303cf68ba82"></a>
SearchMethodSurface&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#af2d27cdd139bd79335008303cf68ba82">search_method_surface_</a></td></tr>
<tr class="memdesc:af2d27cdd139bd79335008303cf68ba82 inherit pro_attribs_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">The search method template for points. <br /></td></tr>
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PointCloudInConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a98f8c497ac78cf49d9274c3ab5fe52df">surface_</a></td></tr>
<tr class="memdesc:a98f8c497ac78cf49d9274c3ab5fe52df inherit pro_attribs_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">An input point cloud describing the surface that is to be used for nearest neighbors estimation. <br /></td></tr>
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KdTreePtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a7ce882e12198b2b2373cc31ba27b0ef1">tree_</a></td></tr>
<tr class="memdesc:a7ce882e12198b2b2373cc31ba27b0ef1 inherit pro_attribs_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the spatial search object. <br /></td></tr>
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double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a0d21af8f0a11aa224026f6bb8e3060e7">search_parameter_</a></td></tr>
<tr class="memdesc:a0d21af8f0a11aa224026f6bb8e3060e7 inherit pro_attribs_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">The actual search parameter (from either <em>search_radius_</em> or <em>k_</em>). <br /></td></tr>
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double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a2c52e9b0412b8ce790837b24cd99f0af">search_radius_</a></td></tr>
<tr class="memdesc:a2c52e9b0412b8ce790837b24cd99f0af inherit pro_attribs_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">The nearest neighbors search radius for each point. <br /></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#a3f68793061ef0973bdacfea56cf5ae21">k_</a></td></tr>
<tr class="memdesc:a3f68793061ef0973bdacfea56cf5ae21 inherit pro_attribs_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">The number of K nearest neighbors to use for each point. <br /></td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_feature.html#aa08fc132189062dabfa291701fa46440">fake_surface_</a></td></tr>
<tr class="memdesc:aa08fc132189062dabfa291701fa46440 inherit pro_attribs_classpcl_1_1_feature"><td class="mdescLeft">&#160;</td><td class="mdescRight">If no surface is given, we use the input <a class="el" href="classpcl_1_1_point_cloud.html" title="PointCloud represents the base class in PCL for storing collections of 3D points.">PointCloud</a> as the surface. <br /></td></tr>
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<tr class="inherit_header pro_attribs_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Protected 属性 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointInT &gt;</a></td></tr>
<tr class="memitem:a09c70d8e06e3fb4f07903fe6f8d67869 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a09c70d8e06e3fb4f07903fe6f8d67869"></a>
PointCloudConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a></td></tr>
<tr class="memdesc:a09c70d8e06e3fb4f07903fe6f8d67869 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">The input point cloud dataset. <br /></td></tr>
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IndicesPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a></td></tr>
<tr class="memdesc:aaee847c8a517ebf365bad2cb182a6626 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the vector of point indices to use. <br /></td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#ada1eadb824d34ca9206a86343d9760bb">use_indices_</a></td></tr>
<tr class="memdesc:ada1eadb824d34ca9206a86343d9760bb inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set to true if point indices are used. <br /></td></tr>
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<tr class="memitem:adadb0299f144528020ed558af6879662 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="adadb0299f144528020ed558af6879662"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#adadb0299f144528020ed558af6879662">fake_indices_</a></td></tr>
<tr class="memdesc:adadb0299f144528020ed558af6879662 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. <br /></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;typename PointInT, typename PointNT, typename PointOutT&gt;<br />
class pcl::SpinImageEstimation&lt; PointInT, PointNT, PointOutT &gt;</h3>

<p>Estimates spin-image descriptors in the given input points. </p>
<p>This class represents spin image descriptor. Spin image is a histogram of point locations summed along the bins of the image. A 2D accumulator indexed by <em>a</em> and <em>b</em> is created. Next, the coordinates (<em>a</em>, <em>b</em>) are computed for a vertex in the surface mesh that is within the support of the spin image (explained below). The bin indexed by (<em>a</em>, <em>b</em>) in the accumulator is then incremented; bilinear interpolation is used to smooth the contribution of the vertex. This procedure is repeated for all vertices within the support of the spin image. The resulting accumulator can be thought of as an image; dark areas in the image correspond to bins that contain many projected points. As long as the size of the bins in the accumulator is greater than the median distance between vertices in the mesh (the definition of mesh resolution), the position of individual vertices will be averaged out during spin image generation.</p>
<dl class="section attention"><dt>注意</dt><dd>The input normals given by <a class="el" href="classpcl_1_1_spin_image_estimation.html#aa847219e3000ed6a1dd73509bcc318e4">setInputNormals</a> have to match the input point cloud given by <a class="el" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a>. This behavior is different than feature estimation methods that extend <a class="el" href="classpcl_1_1_feature_from_normals.html">FeatureFromNormals</a>, which match the normals with the search surface.</dd></dl>
<p>With the default paramters, pcl::Histogram&lt;153&gt; is a good choice for PointOutT. Of course the dimension of this descriptor must change to match the number of bins set by the parameters.</p>
<p>For further information please see:</p>
<ul>
<li>Johnson, A. E., &amp; Hebert, M. (1998). Surface Matching for <a class="el" href="class_object.html">Object</a> Recognition in Complex 3D Scenes. Image and Vision Computing, 16, 635-651.</li>
</ul>
<p>The class also implements radial spin images and spin-images in angular domain (or both).</p>
<dl class="section author"><dt>作者</dt><dd>Roman Shapovalov, Alexander Velizhev </dd></dl>
</div><h2 class="groupheader">构造及析构函数说明</h2>
<a id="ab66e696b17513a417f97e39aa399f73e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ab66e696b17513a417f97e39aa399f73e">&#9670;&nbsp;</a></span>SpinImageEstimation()</h2>

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<div class="memtemplate">
template&lt;typename PointInT , typename PointNT , typename PointOutT &gt; </div>
      <table class="memname">
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          <td class="memname"><a class="el" href="classpcl_1_1_spin_image_estimation.html">pcl::SpinImageEstimation</a>&lt; PointInT, PointNT, PointOutT &gt;::<a class="el" href="classpcl_1_1_spin_image_estimation.html">SpinImageEstimation</a> </td>
          <td>(</td>
          <td class="paramtype">unsigned int&#160;</td>
          <td class="paramname"><em>image_width</em> = <code>8</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">double&#160;</td>
          <td class="paramname"><em>support_angle_cos</em> = <code>0.0</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">unsigned int&#160;</td>
          <td class="paramname"><em>min_pts_neighb</em> = <code>0</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
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<p>Constructs empty spin image estimator. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">image_width</td><td>spin-image resolution, number of bins along one dimension </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">support_angle_cos</td><td>minimal allowed cosine of the angle between the normals of input point and search surface point for the point to be retained in the support </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">min_pts_neighb</td><td>min number of points in the support to correctly estimate spin-image. If at some point the support contains less points, exception is thrown </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;                                                                                   :</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;  input_normals_ (), rotation_axes_cloud_ (), </div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;  is_angular_ (<span class="keyword">false</span>), rotation_axis_ (), use_custom_axis_(<span class="keyword">false</span>), use_custom_axes_cloud_ (<span class="keyword">false</span>), </div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;  is_radial_ (<span class="keyword">false</span>), image_width_ (image_width), support_angle_cos_ (support_angle_cos), </div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  min_pts_neighb_ (min_pts_neighb)</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;{</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;  assert (support_angle_cos_ &lt;= 1.0 &amp;&amp; support_angle_cos_ &gt;= 0.0); <span class="comment">// may be permit negative cosine?</span></div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160; </div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;  <a class="code" href="classpcl_1_1_feature.html#a54032b79551164878ff59ed93b5c1dc5">feature_name_</a> = <span class="stringliteral">&quot;SpinImageEstimation&quot;</span>;</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1_feature_html_a54032b79551164878ff59ed93b5c1dc5"><div class="ttname"><a href="classpcl_1_1_feature.html#a54032b79551164878ff59ed93b5c1dc5">pcl::Feature::feature_name_</a></div><div class="ttdeci">std::string feature_name_</div><div class="ttdoc">The feature name.</div><div class="ttdef"><b>Definition:</b> feature.h:222</div></div>
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<h2 class="groupheader">成员函数说明</h2>
<a id="ab09ec6b20fc126a9e2f1ab19fee51286"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ab09ec6b20fc126a9e2f1ab19fee51286">&#9670;&nbsp;</a></span>computeFeature()</h2>

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template&lt;typename PointInT , typename PointNT , typename PointOutT &gt; </div>
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          <td class="memname">void <a class="el" href="classpcl_1_1_spin_image_estimation.html">pcl::SpinImageEstimation</a>&lt; PointInT, PointNT, PointOutT &gt;::computeFeature </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="classpcl_1_1_point_cloud.html">PointCloudOut</a> &amp;&#160;</td>
          <td class="paramname"><em>output</em></td><td>)</td>
          <td></td>
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<span class="mlabels"><span class="mlabel">protected</span><span class="mlabel">virtual</span></span>  </td>
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<p>Estimate the Spin Image descriptors at a set of points given by setInputWithNormals() using the surface in setSearchSurfaceWithNormals() and the spatial locator </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>the resultant point cloud that contains the Spin Image feature estimates </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1_feature.html#ace6344a05ab920294e725ef503cac0c0">pcl::Feature&lt; PointInT, PointOutT &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;{ </div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i_input = 0; i_input &lt; static_cast&lt;int&gt; (<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;size ()); ++i_input)</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;  {</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;    Eigen::ArrayXXd res = <a class="code" href="classpcl_1_1_spin_image_estimation.html#a3144eb10e31eb625d1e0faaeee278e26">computeSiForPoint</a> (<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;at (i_input));</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160; </div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;    <span class="comment">// Copy into the resultant cloud</span></div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> iRow = 0; iRow &lt; res.rows () ; iRow++)</div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;    {</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> iCol = 0; iCol &lt; res.cols () ; iCol++)</div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;      {</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;        output.points[i_input].histogram[ iRow*res.cols () + iCol ] = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (res (iRow, iCol));</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;      }</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;    }   </div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;  } </div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_aaee847c8a517ebf365bad2cb182a6626"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">pcl::PCLBase&lt; PointInT &gt;::indices_</a></div><div class="ttdeci">IndicesPtr indices_</div><div class="ttdoc">A pointer to the vector of point indices to use.</div><div class="ttdef"><b>Definition:</b> pcl_base.h:153</div></div>
<div class="ttc" id="aclasspcl_1_1_spin_image_estimation_html_a3144eb10e31eb625d1e0faaeee278e26"><div class="ttname"><a href="classpcl_1_1_spin_image_estimation.html#a3144eb10e31eb625d1e0faaeee278e26">pcl::SpinImageEstimation::computeSiForPoint</a></div><div class="ttdeci">Eigen::ArrayXXd computeSiForPoint(int index) const</div><div class="ttdoc">Computes a spin-image for the point of the scan.</div><div class="ttdef"><b>Definition:</b> spin_image.hpp:69</div></div>
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<a id="a3144eb10e31eb625d1e0faaeee278e26"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a3144eb10e31eb625d1e0faaeee278e26">&#9670;&nbsp;</a></span>computeSiForPoint()</h2>

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<div class="memtemplate">
template&lt;typename PointInT , typename PointNT , typename PointOutT &gt; </div>
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          <td class="memname">Eigen::ArrayXXd <a class="el" href="classpcl_1_1_spin_image_estimation.html">pcl::SpinImageEstimation</a>&lt; PointInT, PointNT, PointOutT &gt;::computeSiForPoint </td>
          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>index</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Computes a spin-image for the point of the scan. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">index</td><td>the index of the reference point in the input cloud </td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>返回</dt><dd>estimated spin-image (or its variant) as a matrix </dd></dl>
<div class="fragment"><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;{</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  assert (image_width_ &gt; 0);</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;  assert (support_angle_cos_ &lt;= 1.0 &amp;&amp; support_angle_cos_ &gt;= 0.0); <span class="comment">// may be permit negative cosine?</span></div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160; </div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;  <span class="keyword">const</span> Eigen::Vector3f origin_point (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[index].getVector3fMap ());</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160; </div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;  Eigen::Vector3f origin_normal;</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  origin_normal = </div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    input_normals_ ? </div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;      input_normals_-&gt;points[index].getNormalVector3fMap () :</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;      Eigen::Vector3f (); <span class="comment">// just a placeholder; should never be used!</span></div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160; </div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;  <span class="keyword">const</span> Eigen::Vector3f rotation_axis = use_custom_axis_ ? </div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    rotation_axis_.getNormalVector3fMap () : </div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    use_custom_axes_cloud_ ?</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;      rotation_axes_cloud_-&gt;points[index].getNormalVector3fMap () :</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;      origin_normal;  </div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160; </div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;  Eigen::ArrayXXd m_matrix (Eigen::ArrayXXd::Zero (image_width_+1, 2*image_width_+1));</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;  Eigen::ArrayXXd m_averAngles (Eigen::ArrayXXd::Zero (image_width_+1, 2*image_width_+1));</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160; </div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  <span class="comment">// OK, we are interested in the points of the cylinder of height 2*r and</span></div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;  <span class="comment">// base radius r, where r = m_dBinSize * in_iImageWidth</span></div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;  <span class="comment">// it can be embedded to the sphere of radius sqrt(2) * m_dBinSize * in_iImageWidth</span></div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;  <span class="comment">// suppose that points are uniformly distributed, so we lose ~40%</span></div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;  <span class="comment">// according to the volumes ratio</span></div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;  <span class="keywordtype">double</span> bin_size = 0.0;</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;  <span class="keywordflow">if</span> (is_radial_)</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    bin_size = <a class="code" href="classpcl_1_1_feature.html#a2c52e9b0412b8ce790837b24cd99f0af">search_radius_</a> / image_width_;  </div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    bin_size = <a class="code" href="classpcl_1_1_feature.html#a2c52e9b0412b8ce790837b24cd99f0af">search_radius_</a> / image_width_ / sqrt(2.0);</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160; </div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;  std::vector&lt;int&gt; nn_indices;</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;  std::vector&lt;float&gt; nn_sqr_dists;</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> neighb_cnt = this-&gt;<a class="code" href="classpcl_1_1_feature.html#aa7d2ff6f0db4d63a74a3e01ad2b1f9ab">searchForNeighbors</a> (index, <a class="code" href="classpcl_1_1_feature.html#a2c52e9b0412b8ce790837b24cd99f0af">search_radius_</a>, nn_indices, nn_sqr_dists);</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;  <span class="keywordflow">if</span> (neighb_cnt &lt; <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (min_pts_neighb_))</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;  {</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    <span class="keywordflow">throw</span> PCLException (</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;      <span class="stringliteral">&quot;Too few points for spin image, use setMinPointCountInNeighbourhood() to decrease the threshold or use larger feature radius&quot;</span>,</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;      <span class="stringliteral">&quot;spin_image.hpp&quot;</span>, <span class="stringliteral">&quot;computeSiForPoint&quot;</span>);</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;  }</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160; </div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;  <span class="comment">// for all neighbor points</span></div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i_neigh = 0; i_neigh &lt; neighb_cnt ; i_neigh++)</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;  {</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    <span class="comment">// first, skip the points with distant normals</span></div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    <span class="keywordtype">double</span> cos_between_normals = -2.0; <span class="comment">// should be initialized if used</span></div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    <span class="keywordflow">if</span> (support_angle_cos_ &gt; 0.0 || is_angular_) <span class="comment">// not bogus</span></div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    {</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;      cos_between_normals = origin_normal.dot (input_normals_-&gt;points[nn_indices[i_neigh]].getNormalVector3fMap ());</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;      <span class="keywordflow">if</span> (fabs (cos_between_normals) &gt; (1.0 + 10*std::numeric_limits&lt;float&gt;::epsilon ())) <span class="comment">// should be okay for numeric stability</span></div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;      {      </div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;        PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::computeSiForPoint] Normal for the point %d and/or the point %d are not normalized, dot ptoduct is %f.\n&quot;</span>, </div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;          <a class="code" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> ().c_str (), nn_indices[i_neigh], index, cos_between_normals);</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;        <span class="keywordflow">throw</span> PCLException (<span class="stringliteral">&quot;Some normals are not normalized&quot;</span>,</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;          <span class="stringliteral">&quot;spin_image.hpp&quot;</span>, <span class="stringliteral">&quot;computeSiForPoint&quot;</span>);</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;      }</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;      cos_between_normals = std::max (-1.0, std::min (1.0, cos_between_normals));</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160; </div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;      <span class="keywordflow">if</span> (fabs (cos_between_normals) &lt; support_angle_cos_ )    <span class="comment">// allow counter-directed normals</span></div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;      {</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;      }</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160; </div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;      <span class="keywordflow">if</span> (cos_between_normals &lt; 0.0)</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;      {</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;        cos_between_normals = -cos_between_normals; <span class="comment">// the normal is not used explicitly from now</span></div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;      }</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    }</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    </div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;    <span class="comment">// now compute the coordinate in cylindric coordinate system associated with the origin point</span></div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    <span class="keyword">const</span> Eigen::Vector3f direction (</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;      <a class="code" href="classpcl_1_1_feature.html#a98f8c497ac78cf49d9274c3ab5fe52df">surface_</a>-&gt;points[nn_indices[i_neigh]].getVector3fMap () - origin_point);</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">double</span> direction_norm = direction.norm ();</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    <span class="keywordflow">if</span> (fabs(direction_norm) &lt; 10*std::numeric_limits&lt;double&gt;::epsilon ())  </div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;      <span class="keywordflow">continue</span>;  <span class="comment">// ignore the point itself; it does not contribute really</span></div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    assert (direction_norm &gt; 0.0);</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160; </div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="comment">// the angle between the normal vector and the direction to the point</span></div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    <span class="keywordtype">double</span> cos_dir_axis = direction.dot(rotation_axis) / direction_norm;</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    <span class="keywordflow">if</span> (fabs(cos_dir_axis) &gt; (1.0 + 10*std::numeric_limits&lt;float&gt;::epsilon())) <span class="comment">// should be okay for numeric stability</span></div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    {      </div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;      PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::computeSiForPoint] Rotation axis for the point %d are not normalized, dot ptoduct is %f.\n&quot;</span>, </div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;        <a class="code" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> ().c_str (), index, cos_dir_axis);</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;      <span class="keywordflow">throw</span> PCLException (<span class="stringliteral">&quot;Some rotation axis is not normalized&quot;</span>,</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;        <span class="stringliteral">&quot;spin_image.hpp&quot;</span>, <span class="stringliteral">&quot;computeSiForPoint&quot;</span>);</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    }</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    cos_dir_axis = std::max (-1.0, std::min (1.0, cos_dir_axis));</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160; </div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;    <span class="comment">// compute coordinates w.r.t. the reference frame</span></div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;    <span class="keywordtype">double</span> beta = std::numeric_limits&lt;double&gt;::signaling_NaN ();</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;    <span class="keywordtype">double</span> alpha = std::numeric_limits&lt;double&gt;::signaling_NaN ();</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    <span class="keywordflow">if</span> (is_radial_) <span class="comment">// radial spin image structure</span></div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    {</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        beta = asin (cos_dir_axis);  <span class="comment">// yes, arc sine! to get the angle against tangent, not normal!</span></div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;        alpha = direction_norm;</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    }</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    <span class="keywordflow">else</span> <span class="comment">// rectangular spin-image structure</span></div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;    {</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;      beta = direction_norm * cos_dir_axis;</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;      alpha = direction_norm * sqrt (1.0 - cos_dir_axis*cos_dir_axis);</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160; </div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;      <span class="keywordflow">if</span> (fabs (beta) &gt;= bin_size * image_width_ || alpha &gt;= bin_size * image_width_)</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;      {</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;        <span class="keywordflow">continue</span>;  <span class="comment">// outside the cylinder</span></div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;      }</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;    }</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160; </div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    assert (alpha &gt;= 0.0);</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;    assert (alpha &lt;= bin_size * image_width_ + 20 * std::numeric_limits&lt;float&gt;::epsilon () );</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160; </div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160; </div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    <span class="comment">// bilinear interpolation</span></div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    <span class="keywordtype">double</span> beta_bin_size = is_radial_ ? (M_PI / 2 / image_width_) : bin_size;</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    <span class="keywordtype">int</span> beta_bin = int(std::floor (beta / beta_bin_size)) + int(image_width_);</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    assert (0 &lt;= beta_bin &amp;&amp; beta_bin &lt; m_matrix.cols ());</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    <span class="keywordtype">int</span> alpha_bin = int(std::floor (alpha / bin_size));</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;    assert (0 &lt;= alpha_bin &amp;&amp; alpha_bin &lt; m_matrix.rows ());</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160; </div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    <span class="keywordflow">if</span> (alpha_bin == <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (image_width_))  <span class="comment">// border points</span></div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    {</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;      alpha_bin--;</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;      <span class="comment">// HACK: to prevent a &gt; 1</span></div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;      alpha = bin_size * (alpha_bin + 1) - std::numeric_limits&lt;double&gt;::epsilon ();</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;    }</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;    <span class="keywordflow">if</span> (beta_bin == <span class="keywordtype">int</span>(2*image_width_) )  <span class="comment">// border points</span></div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;    {</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;      beta_bin--;</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;      <span class="comment">// HACK: to prevent b &gt; 1</span></div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;      beta = beta_bin_size * (beta_bin - int(image_width_) + 1) - std::numeric_limits&lt;double&gt;::epsilon ();</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    }</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160; </div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;    <span class="keywordtype">double</span> a = alpha/bin_size - double(alpha_bin);</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    <span class="keywordtype">double</span> b = beta/beta_bin_size - double(beta_bin-<span class="keywordtype">int</span>(image_width_)); </div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160; </div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;    assert (0 &lt;= a &amp;&amp; a &lt;= 1);</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    assert (0 &lt;= b &amp;&amp; b &lt;= 1);</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160; </div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;    m_matrix (alpha_bin, beta_bin) += (1-a) * (1-b);</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;    m_matrix (alpha_bin+1, beta_bin) += a * (1-b);</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    m_matrix (alpha_bin, beta_bin+1) += (1-a) * b;</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    m_matrix (alpha_bin+1, beta_bin+1) += a * b;</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160; </div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;    <span class="keywordflow">if</span> (is_angular_)</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;    {</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;      m_averAngles (alpha_bin, beta_bin) += (1-a) * (1-b) * acos (cos_between_normals); </div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;      m_averAngles (alpha_bin+1, beta_bin) += a * (1-b) * acos (cos_between_normals);</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;      m_averAngles (alpha_bin, beta_bin+1) += (1-a) * b * acos (cos_between_normals);</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;      m_averAngles (alpha_bin+1, beta_bin+1) += a * b * acos (cos_between_normals);</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;    }</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;  }</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160; </div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;  <span class="keywordflow">if</span> (is_angular_)</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;  {</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;    <span class="comment">// transform sum to average</span></div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;    m_matrix = m_averAngles / (m_matrix + std::numeric_limits&lt;double&gt;::epsilon ()); <span class="comment">// +eps to avoid division by zero</span></div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;  }</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (neighb_cnt &gt; 1) <span class="comment">// to avoid division by zero, also no need to divide by 1</span></div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;  {</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    <span class="comment">// normalization</span></div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;    m_matrix /= m_matrix.sum();</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;  }</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160; </div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;  <span class="keywordflow">return</span> m_matrix;</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1_feature_html_a2c52e9b0412b8ce790837b24cd99f0af"><div class="ttname"><a href="classpcl_1_1_feature.html#a2c52e9b0412b8ce790837b24cd99f0af">pcl::Feature::search_radius_</a></div><div class="ttdeci">double search_radius_</div><div class="ttdoc">The nearest neighbors search radius for each point.</div><div class="ttdef"><b>Definition:</b> feature.h:239</div></div>
<div class="ttc" id="aclasspcl_1_1_feature_html_a98f8c497ac78cf49d9274c3ab5fe52df"><div class="ttname"><a href="classpcl_1_1_feature.html#a98f8c497ac78cf49d9274c3ab5fe52df">pcl::Feature::surface_</a></div><div class="ttdeci">PointCloudInConstPtr surface_</div><div class="ttdoc">An input point cloud describing the surface that is to be used for nearest neighbors estimation.</div><div class="ttdef"><b>Definition:</b> feature.h:230</div></div>
<div class="ttc" id="aclasspcl_1_1_feature_html_aa7d2ff6f0db4d63a74a3e01ad2b1f9ab"><div class="ttname"><a href="classpcl_1_1_feature.html#aa7d2ff6f0db4d63a74a3e01ad2b1f9ab">pcl::Feature::searchForNeighbors</a></div><div class="ttdeci">int searchForNeighbors(size_t index, double parameter, std::vector&lt; int &gt; &amp;indices, std::vector&lt; float &gt; &amp;distances) const</div><div class="ttdoc">Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface ...</div><div class="ttdef"><b>Definition:</b> feature.h:270</div></div>
<div class="ttc" id="aclasspcl_1_1_feature_html_ae6b4d5717999b6267a670dc704146fdc"><div class="ttname"><a href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">pcl::Feature::getClassName</a></div><div class="ttdeci">const std::string &amp; getClassName() const</div><div class="ttdoc">Get a string representation of the name of this class.</div><div class="ttdef"><b>Definition:</b> feature.h:246</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_a09c70d8e06e3fb4f07903fe6f8d67869"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">pcl::PCLBase&lt; PointInT &gt;::input_</a></div><div class="ttdeci">PointCloudConstPtr input_</div><div class="ttdoc">The input point cloud dataset.</div><div class="ttdef"><b>Definition:</b> pcl_base.h:150</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a05bd9a4e042a5e212c4fac5cc589db95">&#9670;&nbsp;</a></span>initCompute()</h2>

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<div class="memtemplate">
template&lt;typename PointInT , typename PointNT , typename PointOutT &gt; </div>
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          <td class="memname">bool <a class="el" href="classpcl_1_1_spin_image_estimation.html">pcl::SpinImageEstimation</a>&lt; PointInT, PointNT, PointOutT &gt;::initCompute</td>
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<span class="mlabels"><span class="mlabel">protected</span><span class="mlabel">virtual</span></span>  </td>
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<p>initializes computations specific to spin-image. </p>
<dl class="section return"><dt>返回</dt><dd>true iff input data and initialization are correct </dd></dl>

<p>重载 <a class="el" href="classpcl_1_1_feature.html#a2cd0857bae8a4ac67a961d98d9eacde5">pcl::Feature&lt; PointInT, PointOutT &gt;</a> .</p>
<div class="fragment"><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;{</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_feature.html#a2cd0857bae8a4ac67a961d98d9eacde5">Feature&lt;PointInT, PointOutT&gt;::initCompute</a> ())</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;  {</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::initCompute] Init failed.\n&quot;</span>, <a class="code" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;  }</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160; </div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;  <span class="comment">// Check if input normals are set</span></div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;  <span class="keywordflow">if</span> (!input_normals_)</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;  {</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::initCompute] No input dataset containing normals was given!\n&quot;</span>, <a class="code" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;    <a class="code" href="classpcl_1_1_feature.html#ab235b6b76033922b19aae91714d7e413">Feature&lt;PointInT, PointOutT&gt;::deinitCompute</a> ();</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;  }</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160; </div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;  <span class="comment">// Check if the size of normals is the same as the size of the surface</span></div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;  <span class="keywordflow">if</span> (input_normals_-&gt;points.size () != <a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points.size ())</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;  {</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::initCompute] &quot;</span>, <a class="code" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;The number of points in the input dataset differs from &quot;</span>);</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;the number of points in the dataset containing the normals!\n&quot;</span>);</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;    <a class="code" href="classpcl_1_1_feature.html#ab235b6b76033922b19aae91714d7e413">Feature&lt;PointInT, PointOutT&gt;::deinitCompute</a> ();</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;  }</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160; </div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;   <span class="comment">// We need a positive definite search radius to continue</span></div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;  <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_feature.html#a2c52e9b0412b8ce790837b24cd99f0af">search_radius_</a> == 0)</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;  {</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::initCompute] Need a search radius different than 0!\n&quot;</span>, <a class="code" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;    <a class="code" href="classpcl_1_1_feature.html#ab235b6b76033922b19aae91714d7e413">Feature&lt;PointInT, PointOutT&gt;::deinitCompute</a> ();</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;  }</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;  <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_feature.html#a3f68793061ef0973bdacfea56cf5ae21">k_</a> != 0)</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;  {</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::initCompute] K-nearest neighbor search for spin images not implemented. Used a search radius instead!\n&quot;</span>, <a class="code" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;    <a class="code" href="classpcl_1_1_feature.html#ab235b6b76033922b19aae91714d7e413">Feature&lt;PointInT, PointOutT&gt;::deinitCompute</a> ();</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;  }</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;  <span class="comment">// If the surface won&#39;t be set, make fake surface and fake surface normals</span></div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;  <span class="comment">// if we wouldn&#39;t do it here, the following method would alarm that no surface normals is given</span></div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_feature.html#a98f8c497ac78cf49d9274c3ab5fe52df">surface_</a>)</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;  {</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;    <a class="code" href="classpcl_1_1_feature.html#a98f8c497ac78cf49d9274c3ab5fe52df">surface_</a> = <a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>;</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;    <a class="code" href="classpcl_1_1_feature.html#aa08fc132189062dabfa291701fa46440">fake_surface_</a> = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;  }</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160; </div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;  <span class="comment">//if (fake_surface_ &amp;&amp; !input_normals_)</span></div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;  <span class="comment">//  input_normals_ = normals_; // normals_ is set, as checked earlier</span></div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;  </div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;  assert(!(use_custom_axis_ &amp;&amp; use_custom_axes_cloud_));</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160; </div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;  <span class="keywordflow">if</span> (!use_custom_axis_ &amp;&amp; !use_custom_axes_cloud_ <span class="comment">// use input normals as rotation axes</span></div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;    &amp;&amp; !input_normals_)</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;  {</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::initCompute] No normals for input cloud were given!\n&quot;</span>, <a class="code" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;    <span class="comment">// Cleanup</span></div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;    <a class="code" href="classpcl_1_1_feature.html#ab235b6b76033922b19aae91714d7e413">Feature&lt;PointInT, PointOutT&gt;::deinitCompute</a> ();</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;  }</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160; </div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;  <span class="keywordflow">if</span> ((is_angular_ || support_angle_cos_ &gt; 0.0) <span class="comment">// support angle is not bogus NOTE this is for randomly-flipped normals</span></div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;    &amp;&amp; !input_normals_)</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;  {</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::initCompute] No normals for input cloud were given!\n&quot;</span>, <a class="code" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;    <span class="comment">// Cleanup</span></div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;    <a class="code" href="classpcl_1_1_feature.html#ab235b6b76033922b19aae91714d7e413">Feature&lt;PointInT, PointOutT&gt;::deinitCompute</a> ();</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;  }</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160; </div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;  <span class="keywordflow">if</span> (use_custom_axes_cloud_ </div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;    &amp;&amp; rotation_axes_cloud_-&gt;size () == <a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;size ())</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;  {</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::initCompute] Rotation axis cloud have different size from input!\n&quot;</span>, <a class="code" href="classpcl_1_1_feature.html#ae6b4d5717999b6267a670dc704146fdc">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;    <span class="comment">// Cleanup</span></div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;    <a class="code" href="classpcl_1_1_feature.html#ab235b6b76033922b19aae91714d7e413">Feature&lt;PointInT, PointOutT&gt;::deinitCompute</a> ();</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;  }</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160; </div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;  <span class="keywordflow">return</span> (<span class="keyword">true</span>);</div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1_feature_html_a2cd0857bae8a4ac67a961d98d9eacde5"><div class="ttname"><a href="classpcl_1_1_feature.html#a2cd0857bae8a4ac67a961d98d9eacde5">pcl::Feature::initCompute</a></div><div class="ttdeci">virtual bool initCompute()</div><div class="ttdoc">This method should get called before starting the actual computation.</div><div class="ttdef"><b>Definition:</b> feature.hpp:93</div></div>
<div class="ttc" id="aclasspcl_1_1_feature_html_a3f68793061ef0973bdacfea56cf5ae21"><div class="ttname"><a href="classpcl_1_1_feature.html#a3f68793061ef0973bdacfea56cf5ae21">pcl::Feature::k_</a></div><div class="ttdeci">int k_</div><div class="ttdoc">The number of K nearest neighbors to use for each point.</div><div class="ttdef"><b>Definition:</b> feature.h:242</div></div>
<div class="ttc" id="aclasspcl_1_1_feature_html_aa08fc132189062dabfa291701fa46440"><div class="ttname"><a href="classpcl_1_1_feature.html#aa08fc132189062dabfa291701fa46440">pcl::Feature::fake_surface_</a></div><div class="ttdeci">bool fake_surface_</div><div class="ttdoc">If no surface is given, we use the input PointCloud as the surface.</div><div class="ttdef"><b>Definition:</b> feature.h:257</div></div>
<div class="ttc" id="aclasspcl_1_1_feature_html_ab235b6b76033922b19aae91714d7e413"><div class="ttname"><a href="classpcl_1_1_feature.html#ab235b6b76033922b19aae91714d7e413">pcl::Feature::deinitCompute</a></div><div class="ttdeci">virtual bool deinitCompute()</div><div class="ttdoc">This method should get called after ending the actual computation.</div><div class="ttdef"><b>Definition:</b> feature.hpp:176</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a77bac69302ebb759336dfa711dfe24c9">&#9670;&nbsp;</a></span>setAngularDomain()</h2>

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          <td>(</td>
          <td class="paramtype">bool&#160;</td>
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<p>Sets/unsets flag for angular spin-image domain. </p>
<p>Angular spin-image differs from the vanilla one in the way that not the points are collected in the bins but the angles between their normals and the normal to the reference point. For further information please see Endres, F., Plagemann, C., Stachniss, C., &amp; Burgard, W. (2009). Unsupervised Discovery of <a class="el" href="class_object.html">Object</a> Classes from Range Data using Latent Dirichlet Allocation. In Robotics: Science and Systems. Seattle, USA. </p><dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramdir">[in]</td><td class="paramname">is_angular</td><td>true for angular domain, false for point domain </td></tr>
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<div class="fragment"><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;{ is_angular_ = is_angular; }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a93f3f5586e8f01b01a2ea95f77b5d7d6">&#9670;&nbsp;</a></span>setImageWidth()</h2>

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<p>Sets spin-image resolution. </p>
<dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramdir">[in]</td><td class="paramname">bin_count</td><td>spin-image resolution, number of bins along one dimension </td></tr>
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<div class="fragment"><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;      {</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;        image_width_ = bin_count;</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;      }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#aa847219e3000ed6a1dd73509bcc318e4">&#9670;&nbsp;</a></span>setInputNormals()</h2>

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          <td>(</td>
          <td class="paramtype">const PointCloudNConstPtr &amp;&#160;</td>
          <td class="paramname"><em>normals</em></td><td>)</td>
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<p>Provide a pointer to the input dataset that contains the point normals of the input XYZ dataset given by <a class="el" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a> </p>
<dl class="section attention"><dt>注意</dt><dd>The input normals given by <a class="el" href="classpcl_1_1_spin_image_estimation.html#aa847219e3000ed6a1dd73509bcc318e4">setInputNormals</a> have to match the input point cloud given by <a class="el" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a>. This behavior is different than feature estimation methods that extend <a class="el" href="classpcl_1_1_feature_from_normals.html">FeatureFromNormals</a>, which match the normals with the search surface. </dd></dl>
<dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramdir">[in]</td><td class="paramname">normals</td><td>the const boost shared pointer to a <a class="el" href="classpcl_1_1_point_cloud.html" title="PointCloud represents the base class in PCL for storing collections of 3D points.">PointCloud</a> of normals. By convention, L2 norm of each normal should be 1. </td></tr>
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<div class="fragment"><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;      { </div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;        input_normals_ = normals; </div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;      }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#af5a269fd1b1606d4fb90329f7efd5e2a">&#9670;&nbsp;</a></span>setInputRotationAxes()</h2>

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<p>Sets array of vectors as rotation axes for input points. </p>
<p>Useful e.g. when one wants to use tangents instead of normals as rotation axes </p><dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramdir">[in]</td><td class="paramname">axes</td><td>unit-length vectors that serves as rotation axes for the corresponding input points' reference frames </td></tr>
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<div class="fragment"><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;      {</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;        rotation_axes_cloud_ = axes;</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160; </div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;        use_custom_axes_cloud_ = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;        use_custom_axis_ = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;      }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a99c85206d6eabdbaf3aa4dd989d930a7">&#9670;&nbsp;</a></span>setMinPointCountInNeighbourhood()</h2>

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<p>Sets minimal points count for spin image computation. </p>
<dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramdir">[in]</td><td class="paramname">min_pts_neighb</td><td>min number of points in the support to correctly estimate spin-image. If at some point the support contains less points, exception is thrown </td></tr>
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<div class="fragment"><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;      {</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        min_pts_neighb_ = min_pts_neighb;</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;      }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a5e371335fa14ddf04196bf76d720645b">&#9670;&nbsp;</a></span>setRadialStructure()</h2>

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          <td>(</td>
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<p>Sets/unsets flag for radial spin-image structure. </p>
<p>Instead of rectangular coordinate system for reference frame polar coordinates are used. Binning is done depending on the distance and inclination angle from the reference point </p><dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramdir">[in]</td><td class="paramname">is_radial</td><td>true for radial spin-image structure, false for rectangular </td></tr>
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<div class="fragment"><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;{ is_radial_ = is_radial; }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a12e76226cf145a57973c0b37bb80c3f1">&#9670;&nbsp;</a></span>setRotationAxis()</h2>

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<p>Sets single vector a rotation axis for all input points. </p>
<p>It could be useful e.g. when the vertical axis is known. </p><dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramdir">[in]</td><td class="paramname">axis</td><td>unit-length vector that serves as rotation axis for reference frame </td></tr>
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  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;      {</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;        rotation_axis_ = axis;</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;        use_custom_axis_ = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;        use_custom_axes_cloud_ = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;      }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#aec8636459345b81d562ba9bab97dadfd">&#9670;&nbsp;</a></span>setSupportAngle()</h2>

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<p>Sets the maximum angle for the point normal to get to support region. </p>
<dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramdir">[in]</td><td class="paramname">support_angle_cos</td><td>minimal allowed cosine of the angle between the normals of input point and search surface point for the point to be retained in the support </td></tr>
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<div class="fragment"><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;      {</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;        <span class="keywordflow">if</span> (0.0 &gt; support_angle_cos || support_angle_cos &gt; 1.0)  <span class="comment">// may be permit negative cosine?</span></div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;        {</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;          <span class="keywordflow">throw</span> PCLException (<span class="stringliteral">&quot;Cosine of support angle should be between 0 and 1&quot;</span>,</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;            <span class="stringliteral">&quot;spin_image.h&quot;</span>, <span class="stringliteral">&quot;setSupportAngle&quot;</span>);</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;        }</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160; </div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;        support_angle_cos_ = support_angle_cos;</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;      }</div>
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<hr/>该类的文档由以下文件生成:<ul>
<li>features/include/pcl/features/<a class="el" href="spin__image_8h_source.html">spin_image.h</a></li>
<li>features/include/pcl/features/impl/<a class="el" href="spin__image_8hpp_source.html">spin_image.hpp</a></li>
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